Thomas Guyet
Impact in
- Signal Processing top 10%
- Time Series Analysis and Forecasting
- Advanced Malware Detection Techniques
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- Network Security and Intrusion Detection
Papers in
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- Imbalanced Data Classification Techniques 2
- Data Stream Mining Techniques 2
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- Network Security and Intrusion Detection 4
- Co-authors
- René Quiniou (8 shared papers)Florent Masséglia (3 shared papers)Marie-Odile Cordier (3 shared papers)Wei Wang (1 shared paper)Xiangliang Zhang (1 shared paper)Michel Dojat (1 shared paper)Catherine Garbay (1 shared paper)Romain Tavenard (4 shared papers)
- Journals
- Water Resources Research (1 paper)Data Mining and Knowledge Discovery (1 paper)Knowledge-Based Systems (1 paper)European Journal of Cancer (1 paper)Machine Learning (1 paper)
- Partner nations
- FranceUnited KingdomSwitzerland
In The Last Decade
Thomas Guyet
20 papers receiving 264 citations
Peers
Comparison fields: 5 of 80
- Signal Processing 82
- Computer Networks and Communications 76
- Artificial Intelligence 94
- Information Systems 52
- Computational Mathematics 1
Countries citing papers authored by Thomas Guyet
This map shows the geographic impact of Thomas Guyet's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Thomas Guyet with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Thomas Guyet more than expected).
Fields of papers citing papers by Thomas Guyet
This network shows the impact of papers produced by Thomas Guyet. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Thomas Guyet. The network helps show where Thomas Guyet may publish in the future.
Co-authors
The 25 scholars most cited alongside Thomas Guyet, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 73 | |
| 2 | 2021 | 31 | |
| 3 | 2007 | 28 | |
| 4 | 2015 | 28 | |
| 5 | 2022 | 23 | |
| 6 | 2008 | 22 | |
| 7 | 2013 | 21 | |
| 8 | 2018 | 14 | |
| 9 | 2021 | 7 | |
| 10 | 2017 | 5 | |
| 11 | 2022 | 4 | |
| 12 | 2009 | 4 | |
| 13 | 2020 | 2 | |
| 14 | 2022 | 2 | |
| 15 | 2025 | 1 | |
| 16 | Online and adaptive anomaly Detection: detecting intrusions in unlabelled audit data streams. | 2009 | 1 |
| 17 | 2023 | 1 | |
| 18 | 2023 | 1 | |
| 19 | 2015 | 1 | |
| 20 | 2016 | 1 |
About Thomas Guyet
Thomas Guyet is a scholar working on Artificial Intelligence, Computer Networks and Communications, Signal Processing, Information Systems and Radiology, Nuclear Medicine and Imaging, having authored 23 papers that have together received 270 indexed citations. Recurring topics across this work include Time Series Analysis and Forecasting (5 papers), Network Security and Intrusion Detection (4 papers), Data Mining Algorithms and Applications (3 papers), Data Management and Algorithms (2 papers), Imbalanced Data Classification Techniques (2 papers), Land Use and Ecosystem Services (2 papers), Data Stream Mining Techniques (2 papers) and Remote Sensing and LiDAR Applications (2 papers). The work is most often cited by research in Signal Processing (82 citations), Computer Networks and Communications (76 citations), Artificial Intelligence (94 citations), Information Systems (52 citations) and Computational Mathematics (1 citation). Thomas Guyet has collaborated with scholars based in France, United Kingdom and Switzerland. Frequent co-authors include René Quiniou, Florent Masséglia, Marie-Odile Cordier, Wei Wang, Xiangliang Zhang, Michel Dojat, Catherine Garbay, Romain Tavenard, Simon Malinowski and Emmanuelle Kempf. Their work appears in journals such as Water Resources Research, Data Mining and Knowledge Discovery, Knowledge-Based Systems, European Journal of Cancer and Machine Learning.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.